Infrastructure for neural networks

Deep learning, a subset of artificial intelligence (AI), is about enabling computers to learn new concepts from raw data – much like the human mind. A deep learning system, for example, can spot the difference between a flower and a tree after viewing thousands of images of each. Deep learning requires extreme compute, I/O and networks, as well as exponential scaling. Traditional IT infrastructure is inadequate – you need optimal platforms designed with deep expertise.

AI can amplify human capabilities and turn exponentially growing data into insight, action and value – creating your competitive edge. Navigate this fast-changing field and realise the promise of AI, from IoT to cloud to data centre, with a trusted global enterprise partner. Only HPE is delivering on a roadmap to create more powerful, flexible, secure and efficient computing and data architectures, powering AI from edge to cloud to core.

of developer teams will include AI functionality in one or more applications by 2018.1

40%

of all digital transformation initiatives will be enabled by AI by 2019.1

100%

of all effective IoT efforts will be supported by AI capabilities by 2019.1

A range of AI and deep learning capabilities

Regardless of where you are in your AI journey, it’s important to tailor the right solution for your business-specific AI needs. From strategic advising to purpose-built technology, put our AI and deep learning expertise to work for you, unraveling the complexity and creating your ideal, end-to-end AI solution.

If you aren't sure exactly where deep learning fits in the AI puzzle, here are the fundamentals. Deep learning is a kind of machine learning where computers create large artificial neural networks, similar to the human brain. The ability of these networks to think and learn grows as they are trained with learning algorithms and as they process more and more data. Over time, these networks develop many layers of learning – hence the term deep – as well as better performance and more independence.

Although neural nets have existed since the 1950s, only recently have power, processing and storage capabilities developed to the point of being able to support them. Deep learning is a fairly new frontier for enterprise applications, but it holds great promise for smart technology developments in almost every field.

Targeted AI tools and resources

Seeing the potential in AI and implementing an AI solution are two different things. Reach your goals with the right tools for an optimal AI configuration.

“Through our partnership with SGI, and now HPE, the Tokyo Institute of Technology has worked successfully to deliver a converged world-leading HPC and deep learning platform that can address our requirements and those of our nation.”

Innovative tools to accelerate deep learning

AI and deep learning hold the potential to fuel groundbreaking innovation in nearly every industry – if you have the tools and know-how to implement them. Take advantage of our comprehensive, complementary tools and solutions to untangle the complexity and create your end-to-end AI solution, from the core data centre to the intelligent edge.

HPE Artificial Intelligence Transformation Workshop

Dive into the realm of AI with a highly interactive one-day workshop that provides consulting expertise to help you get started with AI, evolve your strategic data and analytics initiatives, and prioritize your AI use cases.

Characterise your deep learning workloads and get a recommendation for the optimal hardware/software stack for your workloads. Components include a Benchmarking Suite for deep learning, reference designs and the HPE Deep Learning Performance Guide.

Speed up the training process for your AI model with massively parallel GPU accelerators. With support for eight high-performance GPUs, the HPE Apollo 6500 Gen10 system slashes AI training time by delivering dramatic increases in application performance.

A liquid cooled, tray-based, scalable, high-density clustered computer system designed to deliver the utmost in performance, density, scale, and efficiency in an easy-to-manage, production-ready platform

A 1U rack-mount dual-socket Intel Xeon server with support for four NVIDIA® Tesla SXM2 GPUs with NVLink, enabling up to 14,336 NVIDIA CUDA cores and 42.4 Tflops of single-precision floating-point performance